A novel hybrid evolutionary approach for capturing decision maker knowledge into the unequal area facility layout problem

• We are concerned with an unequal area facility layout problem.
• Existing approaches are normally based on optimization, which can be insufficient in certain cases.
• Our interactive genetic algorithm involves the decision maker in the search for a suited solution.
• Our new approach based on niching methods is tested with two real problem cases.

Introducing expert knowledge into evolutionary algorithms for the facility layout design problem can provide better solutions than the mathematically optimal solutions by considering qualitative aspects in the design. However, this approach requires the direct intervention of a designer (normally called the decision maker) in the evolutionary algorithm that guides the search process to adjust it to his/her preferences. To do this, the designer scores each of the most representative designs of the population to avoid fatigue. The selection of the solutions to be presented for human assessment is crucial, so a small number of solutions that represents the characteristics of the population must be selected without losing the variability of the solutions. The novel hybrid system proposed in this study consists of an interactive genetic algorithm that is combined with two different niching methods to allow interactions between the algorithm and the expert designer. The inclusion of niching techniques into the approach allows for the preservation of diversity, which avoids presenting similar solutions to the designer in the same iteration of the algorithm. The proposed approach was tested using two case studies of facility layout designs. The results of the experiments, which successfully validate the approach, are presented, compared and discussed.